Array antennas synthesis is one of the most important problems in the optimization of antenna and electromagnetics. In this paper, a recently developed metaheuristic algorithm, known as the Gravitational Search Algorithm (GSA), is employed for the pattern synthesis of linear and non-uniform planar antenna arrays with desired pattern nulls in the interfering directions and minimum side lobe level (SLL) by position-only optimization. Like other nature-inspired algorithms, GSA is also a population-based method and uses a population of solutions to proceed to a global solution. The results of GSA are validated by comparing them with the results obtained using particle swarm optimization (PSO) and some other algorithms reported in literature for linear and planar array. The side-lobe level and null depth obtained from gravitational search algorithm for planar array are improved up to -30 dB and -200 dB, respectively. The results reveal the superior performance of GSA to the other techniques for the design of linear and planar antenna arrays.
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